Cancer is a disease of the genome characterized by substantial variability in clinical course, outcome, and response to therapies. The main factor underlying this variability is the genetic heterogeneity of human cancers. It has been demonstrated that individual tumors of the same histopathological subtype carry different aberrations in their cellular DNA. It is recognized that targeted cancer therapies target specific genetic aberrations rather than histological disease subtypes. Some examples of drugs that target molecular abnormalities are imatinib mesylate (which is used to treat chronic myelogenous leukemia) and trastuzumab (which is used to treat HER2-positive breast cancer).
Currently, pre-clinical models for oncology drug testing are selected based on their availability, adaptability to tumor formation in mice, growth in culture, as well as other parameters. The problem with this approach is that it does not take into account the genetic heterogeneity of the parent tumor. This results in a poor representation of molecular subtypes of tumors during preclinical testing. Thus, the high response rates that are frequently seen in preclinical testing may only represent the response of the molecular subtype represented in the preclinical testing laboratory. If this subtype represents only a fraction of the patient population, and if the drug is efficacious only against this specific subtype, then the response in the clinic will be significantly lower. Therefore, there is a need in the art for improved pre-clinical testing models that better represent all parent tumor types. Such improved pre-clinical testing will increase the predictability of the preclinical testing of new drugs.